Wastewater surveillance (WWS) is useful to better understand the spreading of coronavirus disease 2019 (COVID-19) in communities, which can help design and implement suitable mitigation measures. The main objective of this study was to develop the Wastewater Viral Load Risk Index (WWVLRI) for three Saskatchewan cities to offer a simple metric to interpret WWS. The index was developed by considering relationships between reproduction number, clinical data, daily per capita concentrations of virus particles in wastewater, and weekly viral load change rate. Trends of daily per capita concentrations of SARS-CoV-2 in wastewater for Saskatoon, Prince Albert, and North Battleford were similar during the pandemic, suggesting that per capita viral load can be useful to quantitatively compare wastewater signals among cities and develop an effective and comprehensible WWVLRI. The effective reproduction number (Rt) and the daily per capita efficiency adjusted viral load thresholds of 85 × 106 and 200 × 106 N2 gene counts (gc)/population day (pd) were determined. These values with rates of change were used to categorize the potential for COVID-19 outbreaks and subsequent declines. The weekly average was considered 'low risk' when the per capita viral load was 85 × 106 N2 gc/pd. A 'medium risk' occurs when the per capita copies were between 85 × 106 and 200 × 106 N2 gc/pd. with a rate of change <100 %. The start of an outbreak is indicated by a 'medium-high' risk classification when the week-over-week rate of change was >100 %, and the absolute magnitude of concentrations of viral particles was >85 × 106 N2 gc/pd. Lastly, a 'high risk' occurs when the viral load exceeds 200 × 106 N2 gc/pd. This methodology provides a valuable resource for decision-makers and health authorities, specifically given the limitation of COVID-19 surveillance based on clinical data.

Phosphorus (P) export from urban areas via stormwater runoff contributes to eutrophication of downstream aquatic ecosystems. Bioretention cells are a Low Impact Development (LID) technology promoted as a green solution to attenuate urban peak flow discharge, as well as the export of excess nutrients and other contaminants. Despite their rapidly growing implementation worldwide, a predictive understanding of the efficiency of bioretention cells in reducing urban P loadings remains limited. Here, we present a reaction-transport model to simulate the fate and transport of P in a bioretention cell facility in the greater Toronto metropolitan area. The model incorporates a representation of the biogeochemical reaction network that controls P cycling within the cell. We used the model as a diagnostic tool to determine the relative importance of processes immobilizing P in the bioretention cell. The model predictions were compared to multi-year observational data on 1) the outflow loads of total P (TP) and soluble reactive P (SRP) during the 2012-2017 period, 2) TP depth profiles collected at 4 time points during the 2012-2019 period, and 3) sequential chemical P extractions performed on core samples from the filter media layer obtained in 2019. Results indicate that exfiltration to underlying native soil was principally responsible for decreasing the surface water discharge from the bioretention cell (63 % runoff reduction). From 2012 to 2017, the cumulative outflow export loads of TP and SRP only accounted for 1 % and 2 % of the corresponding inflow loads, respectively, hence demonstrating the extremely high P reduction efficiency of this bioretention cell. Accumulation in the filter media layer was the predominant mechanism responsible for the reduction in P outflow loading (57 % retention of TP inflow load) followed by plant uptake (21 % TP retention). Of the P retained within the filter media layer, 48 % occurred in stable, 41 % in potentially mobilizable, and 11 % in easily mobilizable forms. There were no signs that the P retention capacity of the bioretention cell was approaching saturation after 7 years of operation. The reactive transport modeling approach developed here can in principle be transferred and adapted to fit other bioretention cell designs and hydrological regimes to estimate P surface loading reductions at a range of temporal scales, from a single precipitation event to long-term (i.e., multi-year) operation.